International Journal of Adaptive Control and Signal Processing最新文献

{"title":"Event-Triggered Tracking Control of Nonlinear Nonparametric Systems for Time-Varying Reference Signals","authors":"Xiaoyu Lu,&nbsp;Wenhui Feng,&nbsp;Liying Wang","doi":"10.1002/acs.70090","DOIUrl":"https://doi.org/10.1002/acs.70090","url":null,"abstract":"<div>\u0000 <p>In this paper, we investigate the tracking control problem for nonlinear nonparametric systems. An adaptive control strategy is designed incorporating an event-triggered mechanism, and the average transmission rate of the event detector is obtained. The designed control algorithm is essentially a stochastic approximation algorithm with expanding truncations, in which the inserted event detector decides whether to trigger the update of the control input by setting a threshold value. Under the given assumptions, the proposed control strategy is able to achieve mean tracking performance for both deterministic and stochastic reference signals, which are dealt with in a unified framework for convergence analysis. In addition, the optimality of the proposed control algorithm is established in terms of asymptotic long-run average of squared tracking error. Finally, the correctness of the theoretical results is verified through numerical simulations.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 8","pages":"1599-1613"},"PeriodicalIF":3.8,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148695766","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recursive State Estimation for Complex Networks With Hybrid Attacks via Adaptive Event-Triggered Multichannel Round-Robin Protocol","authors":"Wen Chen,&nbsp;Danqi Zhao,&nbsp;Jiaxing Li,&nbsp;Chaoqing Jia,&nbsp;Jun Hu","doi":"10.1002/acs.70096","DOIUrl":"https://doi.org/10.1002/acs.70096","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper is concerned with the adaptive event-triggered recursive state estimation (SE) issue for a class of nonlinear complex networks (CNs) with hybrid attacks and a multichannel round-robin protocol. A new hybrid scheduling mechanism, referred to as the adaptive event-triggered multichannel round-robin protocol (AET-MRRP), is adopted to regulate data transmission with the hope of saving network resources between sensors and estimators. Bernoulli random sequences with known statistical properties are employed to characterize hybrid attack phenomena. The aim of this paper is to design a recursive SE scheme for nonlinear CNs under the AET-MRRP in the presence of hybrid attacks. Within this framework, the state estimation error covariance (SEEC) is given, and an upper bound (UB) on the SE error is derived. Then, the state estimator gain matrix is parameterized by optimizing the trace of the UB. Under specific assumptions, the mean square exponential boundedness of SEEC is verified. Finally, the effectiveness of the proposed recursive SE method is demonstrated through a simulation example.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 8","pages":"1668-1687"},"PeriodicalIF":3.8,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148696418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Low-Order Integrated Guidance and Control Scheme for Reentry Vehicle Based on Dual-Loop Controller","authors":"Lei Cui,&nbsp;Zhe Li,&nbsp;Zhicheng Zhang","doi":"10.1002/acs.70086","DOIUrl":"https://doi.org/10.1002/acs.70086","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, a low-order integrated guidance and control (LOIGC) scheme is designed for Bank To Turn (BTT) reentry vehicle with impact angle constraints. First, the model of the LOIGC scheme is obtained by combining the three-channel body rates and acceleration components of the reentry vehicle in the ballistic frame. The LOIGC model can be divided into two subsystems: body line-of-sight (LOS) angle subsystem and body rates subsystem. Second, a dual-loop controller is designed for reentry vehicle with impact angle constraints. In order to lead the vehicle to attack target with desired impact angles, a model predictive controller (MPC) is designed for outer loop, the body rates of the three channels are utilized as pseudo-inputs. Then the commands of fin deflections are obtained by the inner controller, which is designed using predefined-time sliding mode control (SMC) and predefined-time extended state observer (ESO). Finally, the effectiveness of the algorithm proposed in this paper is validated through the six-degree-of-freedom (6DOF) simulation.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 8","pages":"1731-1742"},"PeriodicalIF":3.8,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148696573","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributed Formation Splitting and Merging for Multiple UAVs With Actuator Faults Under Cooperation-Antagonism Interactions","authors":"Peng Liu,&nbsp;Shengxian Cao","doi":"10.1002/acs.70088","DOIUrl":"https://doi.org/10.1002/acs.70088","url":null,"abstract":"<div>\u0000 \u0000 <p>In this paper, a formation splitting and merging problem for multiple quadrotor UAVs with actuator faults is investigated. A fully distributed neural fault-tolerant formation splitting and merging control algorithm is designed. Under the leading-following framework, the formation splitting and merging maneuver of multiple UAVs can be achieved by assigning cooperation or antagonism between any two UAVs, without the need to plan paths for all agents. Firstly, a distributed finite-time estimator is proposed for some follower UAVs that can't obtain the leader's velocity. Then, the introduction of adaptive dynamic gain avoids the controller's dependence on the global topology information, while also addressing the impact caused by partial loss-of-effectiveness faults. Additionally, adaptive mechanisms and RBF-NN with a single parameter learning law are used to deal with unknown but bounded control input of the leader, disturbance, bias faults, and nonlinearity in the system dynamics. Finally, the effectiveness of the proposed formation control scheme is verified by simulation.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 8","pages":"1573-1583"},"PeriodicalIF":3.8,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148695756","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stability Analysis of Discrete Adaptive Control With Adaptive Control Allocation for Uncertain Systems","authors":"Nathaniel Sisson,&nbsp;K. Merve Dogan","doi":"10.1002/acs.70091","DOIUrl":"https://doi.org/10.1002/acs.70091","url":null,"abstract":"<div>\u0000 \u0000 <p>An over-actuated system is a control system in which the number of available independent actuators exceeds the number of independent control variables required to achieve the desired system behavior. This redundancy allows multiple actuator combinations to generate the same control effect, enabling flexibility in allocation strategies. Yet, unknown actuator degradation in over-actuated systems presents a challenge in controlling uncertain systems. Systems with unknown actuator degradation require designing an adaptive dynamic control allocation method. Also, the presence of uncertain dynamics introduces an additional difficulty to the controlled system's stability. This article presents a discrete-time adaptive solution for uncertain systems with unknown actuator degradation since discrete-time control design has advantages over continuous ones (e.g., naturally suited for digital hardware implementation, and avoids quantization issues and stability margin loss by eliminating discretization). A comprehensive Lyapunov stability analysis is provided to prove closed-loop stability and reference model tracking for the considered system. Numerical results of the simulation on both hexacopter rotational and Aero-Data Model in Research Environment (ADMIRE) dynamics are provided to illustrate the effectiveness of the proposed control architecture.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 8","pages":"1688-1708"},"PeriodicalIF":3.8,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148696594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fractional Second Order Reaching Law-based Sliding Mode Control for Assistive Robotics","authors":"Fatma Abdelhedi,&nbsp;Achraf Derbel,&nbsp;Chadia Zayane,&nbsp;Ahmed Said Nouri,&nbsp;Nabil Derbel","doi":"10.1002/acs.70095","DOIUrl":"https://doi.org/10.1002/acs.70095","url":null,"abstract":"<div>\u0000 <p>Lower-limb rehabilitation exoskeletons must deliver accurate gait assistance while operating under nonlinear dynamics, bounded disturbances, and time-varying human-robot interaction that can amplify transient torque peaks and degrade comfort. This paper proposes a Fractional Second-Order Reaching Law (FSO-RL) sliding mode control strategy that explicitly shapes the reaching phase to obtain fast and well-damped convergence to the sliding manifold while mitigating high-frequency torque oscillations. The method couples a fractional-order sliding variable with a second-order reaching dynamics, providing additional degrees of freedom to regulate transient behavior without sacrificing sliding-mode robustness. A Lyapunov-based analysis is developed to establish reachability and closed-loop convergence in the presence of bounded disturbance torques. The approach is evaluated in simulation on a three-degree-of-freedom lower-limb exoskeleton model using clinically relevant pediatric gait trajectories. Comparative results against a first-order fractional reaching-law baseline show that the proposed FSO-RL controller preserves tracking accuracy while significantly improving torque smoothness and reducing control effort, yielding approximately a 30% reduction in torque-based effort measures over the gait cycle. These results indicate that second-order reaching dynamics combined with fractional-order effects provide an effective mechanism for comfort-oriented exoskeleton assistance under uncertainty.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 8","pages":"1656-1667"},"PeriodicalIF":3.8,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148696419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Quantum Kernel Self-Attention Network With Exponentially Weighted Laguerre Functions for Model Predictive Control","authors":"Rajashree Raghavan,&nbsp;Susy Thomas","doi":"10.1002/acs.70075","DOIUrl":"https://doi.org/10.1002/acs.70075","url":null,"abstract":"<div>\u0000 \u0000 <p>The real-time applicability of Model Predictive Control (MPC) techniques has expanded due to significant advancements in both theoretical and high-performance computing. However, when linear models are applied to multivariable systems with strong nonlinearities and coupled dynamics, practically implementable MPC techniques still encounter issues, including excessive computational complexity, numerical ill-conditioning, and reduced performance. The absence of a methodical and effective strategy for selecting controller parameters that strikes a balance between tracking precision and computational efficiency under rapidly changing operational conditions is another challenge. To address these limitations, this manuscript proposes an Exponentially Weighted Laguerre function based Linear Time Varying Model Predictive Controller (EWLLTVMPC). The computational load is greatly reduced by using Laguerre functions to parameterize the control sequence, and numerical ill-conditioning due to large prediction horizons in multivariable systems is reduced by adding exponential weighting. In addition, the Quantum Kernel Self-Attention Network (QKSAN) model is employed to optimally tune the MPC controller parameters, enabling adaptive and high-performance control under diverse operating scenarios. The main goals of the proposed strategy are to reduce tracking error and control effort while maintaining closed-loop stability. A laboratory-scale Twin Rotor Multi-Input Multi-Output System (TRMS) is used to experimentally test the control optimization model, which is implemented in MATLAB. With RMSE values as low as 0.0057 rad for pitch and 0.0151 rad for yaw, the controller offers improved transient responsiveness. Experimental results demonstrate a 32% reduction in control effort for yaw tracking with little overshoots. The control signals retain their boundedness and smoothness in the face of external perturbations, demonstrating efficient actuator use and dependable performance. Thus, the proposed method shows improved performance compared to traditional Linear Time-Varying MPC, Recursive Least Squares Algorithm (RLSA), Halton Sampling Algorithm (HSA), and Convolutional Neural Network (CNN) approaches.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 8","pages":"1584-1598"},"PeriodicalIF":3.8,"publicationDate":"2026-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148695992","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint Parameter and State Estimation of Errors-in-Variables Nonlinear Systems Based on the Adaptive Kalman Filter","authors":"Jingsheng Chen,&nbsp;Xiao Zhang,&nbsp;Feng Ding","doi":"10.1002/acs.70078","DOIUrl":"https://doi.org/10.1002/acs.70078","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper develops a hybrid strategy for identifying the nonlinear errors-in-variables (EIV) Wiener state-space systems subjected to the unknown states. The Wiener nonlinear system with the noisy input is investigated, and a state-space subsystem affected by the process disturbance is considered. The unbiased parameter estimation of the EIV Wiener systems with nonideal observations and polynomial nonlinearities is realized using the proposed bias-compensated recursive least squares algorithm. Specifically, the estimated bias caused by the noisy measurements is eliminated, and the analytic formulas for estimating unmeasurable nonlinear intermediate variables are derived. Furthermore, based on the adaptive Kalman filtering principle, a state observer is designed to simultaneously estimate the subsystem states and the unknown noise variances in the estimated bias. The presented algorithms in the hybrid framework achieve the joint estimation of the parameters and states for EIV Wiener state-space systems. The convergence analysis shows that the parameter estimates can converge to their true values. Finally, a numerical simulation and a quarter-car model simulation demonstrate the effectiveness of the proposed algorithm.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 7","pages":"1441-1462"},"PeriodicalIF":3.8,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148395029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fault Detection Using an Observer for Active Suspension Systems Represented by Takagi-Sugeno Fuzzy Models","authors":"Naoufal El Youssfi,&nbsp;Khalid Badie,&nbsp;Laila Dami","doi":"10.1002/acs.70082","DOIUrl":"https://doi.org/10.1002/acs.70082","url":null,"abstract":"<div>\u0000 \u0000 <p>This work investigates a fault detection strategy for an active suspension system modeled through a Takagi Sugeno (T S) fuzzy representation. The quarter-car configuration is adopted to describe the vertical dynamics under mass variations and road disturbances. A dedicated observer is designed to estimate the system states together with the fault signal, and its gains are obtained from linear matrix inequality (LMI) conditions ensuring an <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msub>\u0000 <mrow>\u0000 <mi>H</mi>\u0000 </mrow>\u0000 <mrow>\u0000 <mi>∞</mi>\u0000 </mrow>\u0000 </msub>\u0000 </mrow>\u0000 <annotation>$$ {H}_{infty } $$</annotation>\u0000 </semantics></math> disturbance-attenuation level. A residual-based indicator is then used to determine the presence of a fault. Simulation results show that the method provides reliable detection performance and remains robust with respect to parameter changes and external excitations.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 7","pages":"1514-1523"},"PeriodicalIF":3.8,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148395202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distributionally Robust Tube-Based Model Predictive Control for Nonlinear Systems","authors":"Aijun Yan,&nbsp;Xin Liu","doi":"10.1002/acs.70080","DOIUrl":"https://doi.org/10.1002/acs.70080","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper presents a distributionally robust tube-based model predictive control method for nonlinear systems affected by external random disturbances. The reference trajectory is computed by solving a rolling optimization problem for the nominal system, while an auxiliary controller with chance constraints is solved in real time to guarantee that the trajectory of the disturbed system remains within an invariant tube centered on the reference trajectory. Since the distribution information of disturbances is unknown, a distributionally robust ambiguity set is constructed based on disturbance samples collected online to reformulate the chance constraints, thereby ensuring that the state of the disturbed system satisfies the state constraints with a certain probability. It is demonstrated that this method can ensure the disturbed system remains stable, with its state staying near the reference trajectory. Furthermore, its robustness and compliance with constraints have been validated on a nonlinear continuous stirred-tank reactor.</p>\u0000 </div>","PeriodicalId":50347,"journal":{"name":"International Journal of Adaptive Control and Signal Processing","volume":"40 7","pages":"1473-1485"},"PeriodicalIF":3.8,"publicationDate":"2026-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148395200","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}